Agricultural seed sensing and control system

ABSTRACT

An example agricultural machine comprises a material distribution system that includes a material distribution line configured to convey particulate material to a component. The agricultural machine comprises a sensing system that includes a first sensor configured to generate a first sensor signal indicative of a measure of a flow of the particulate material in the material distribution line, a second sensor configured to generate a second sensor signal indicative of a measure of the flow of the particulate material in the material distribution line, and a correlation generation component configured to receive indications of the first and second sensor signals and to generate a correlation metric that represents a correlation between the first and second sensor signals. In one example, the correlation metric is applied to a sensor signal from a second material distribution line to determine a flow rate in the second material distribution line.

FIELD OF THE DESCRIPTION

The present description generally relates to sensing systems for sensinga material flow rate. More specifically, but not by limitation, thepresent description relates to sensing system for an agriculturalmachine that is configured to sense a quantity or flow rate of anagricultural product (e.g., seeds) through a distribution line.

BACKGROUND

Some agricultural machines, as well as some machines in non-agriculturalapplications, include a distribution system for distributing product toone or more end point components. An example distribution systemcomprises a pneumatic distribution system that utilizes air underpressure to convey particulate material to the one or more end pointcomponents.

In an example agricultural application, an air seeder uses an airdistribution system comprises an air source that provides air flow to aplurality of distribution lines or runs. A metering system, such as avolumetric meter, is used to meter particulate material or other product(e.g., seed, fertilizer, etc.) into the air flow. A controller controlsthe metering system to meter the product at a desired flow rate.

The discussion above is merely provided for general backgroundinformation and is not intended to be used as an aid in determining thescope of the claimed subject matter.

SUMMARY

An example agricultural machine comprises a material distribution systemthat includes a material distribution line configured to conveyparticulate material to a component. The agricultural machine comprisesa sensing system that includes a first sensor configured to generate afirst sensor signal indicative of a measure of a flow of the particulatematerial in the material distribution line, a second sensor configuredto generate a second sensor signal indicative of a measure of the flowof the particulate material in the material distribution line, and acorrelation generation component configured to receive indications ofthe first and second sensor signals and to generate a correlation metricthat represents a correlation between the first and second sensorsignals. In one example, the correlation metric is applied to a sensorsignal from a second material distribution line to determine a flow ratein the second material distribution line.

An example method performed by an agricultural machine comprisesreceiving a first sensor signal from a first sensor that senses a firstflow of particulate material along a first material distribution line,receiving a second sensor signal from a second sensor that senses thefirst flow of particulate material along the first material distributionline, generating a correlation metric that represents a correlationbetween the first sensor signal and the second sensor signal, receivinga third sensor signal from a third sensor that senses a second flow ofparticulate material along a second material distribution line,determining a rate of the second flow by applying the correlation metricto the third sensor signal, and generating a control signal thatcontrols the agricultural machine based on the determined rate.

An example agricultural machine comprises a distribution system includesa first distribution line configured to convey a first seed flow to afirst component and a second distribution line configured to convey asecond seed flow to a second component. The agricultural machinecomprises a metering system configured to meter seeds into the first andsecond distribution lines and a seed sensing system. The seed sensingsystem comprises a first seed sensor configured to generate a firstsensor signal indicative of the first seed flow, a second seed sensorconfigured to generate a second sensor signal indicative of the firstseed flow, a correlation generation component configured to receiveindications of the first and second sensor signals and generate acorrelation metric that represents a correlation between the firstsensor signal and the second sensor signal, a third seed sensorconfigured to generate a third sensor signal indicative of the secondseed flow, and a correlation application component configured todetermine a rate of the second seed flow based on applying thecorrelation metric to the third sensor signal. The agricultural machinecomprises a control system configured to generate a control signal thatcontrols the agricultural machine based on the determined rate.

This Summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This Summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intended tobe used as an aid in determining the scope of the claimed subjectmatter. The claimed subject matter is not limited to implementationsthat solve any or all disadvantages noted in the background.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a side view of one example of an agricultural machinefor distributing agricultural product.

FIG. 2 illustrates a top view of one example of an agricultural machinefor distributing agricultural product.

FIG. 3 is a schematic diagram illustrating one example of anagricultural machine architecture.

FIG. 4 is a flow diagram illustrating an example method for generatingcorrelation metrics from seed sensor signals.

FIG. 5 is a flow diagram illustrating an example method for applyingcorrelation metrics to a seed sensor signal to extrapolate seed flowrate.

FIG. 6 is a block diagram of one example of the architecture illustratedin FIG. 3, deployed in a remote server architecture.

FIGS. 7-9 are examples of mobile devices that can be used in thearchitectures illustrated in the previous figures.

FIG. 10 is a block diagram of one example of a computing environmentthat can be used in the architectures shown in the previous figures.

DETAILED DESCRIPTION

The present disclosure generally relates to sensing systems for sensinga material flow rate. More specifically, but not by limitation, thepresent description relates to a sensing system for an agriculturalmachine that is configured to sense a flow rate, or quantity/count, ofan agricultural product (e.g., seeds) through a distribution line.

In one agricultural example, seeds are conveyed along a seeddistribution line to an endpoint component, and are sensed (e.g.,counted) by a seed sensing system which generates a signal indicative ofthe sensed flow rate or count. The seeds are conveyed to an end pointcomponent, such as a row unit, which disburses the seeds onto or intothe ground. One example includes a ground-engaging opener which placesthe seeds into a furrow. The seed distribution system can comprise apneumatic distribution system that utilizes air under pressure to conveyseeds to the row unit. Alternatively, or in addition, other conveyancemechanism, such as mechanical and/or gravity drop conveyance mechanismscan be utilized.

The sensed flow rate can be utilized in a variety of differentprocesses. For example, the sensed flow rate can be utilized to controla metering system to meter the seeds at a desired flow rate.Alternatively, or in addition, the sensed flow rate can be provided to auser, such as an operator of the agricultural machine for display and/ormanual control of the metering system. The agricultural machine caninclude or generate user interface(s) with user input mechanism(s)utilized by the operator to control and manipulate the agriculturalmachine, such as by adjusting the settings or other operation of themetering system to change the seed flow rate. User input mechanisms canbe rendered via a visual display and/or audio input/output mechanisms.It is noted that, in one example, user interfaces are generated in anoperator compartment of the agricultural machine. For example, a widevariety of user interface components to be provided such as, but notlimited to, levers, switches, wheels, joysticks, buttons, a steeringwheel, pedals, etc. The mechanisms can also include microphones withspeech recognition systems and natural language processing systems, toprocess speech inputs.

The sensed flow rate can also be provided to a remote computing systemand/or other agricultural machine(s) for storage and/or analysis. These,of course, are by way of example only.

It is noted that while examples of a material sensing system aredescribed herein in the context of sensing a flow rate of seeds on anagricultural seeding machine, the described concepts can be utilized ina wide variety of other applications, including both agricultural andnon-agricultural applications. For example, in the context of anotheragricultural application, the material sensing system can sense othertypes of particulate material, such as fertilizer, herbicides,pesticides, etc. Further, the material sensing system can be utilized inautomotive applications, construction applications, industrialapplications, to name a few, that require the sensing of material flowrate. Before discussing the material sensing system in further detail,example agricultural product distribution machines will be described.

FIG. 1 illustrates a side view of one example of an agricultural productdistribution machine for distributing agricultural product in the formof seed, or other particulate material. In the illustrated example, themachine comprises an air seeder 100 that pneumatically delivers (e.g.,using forced air from a blower) seed to ground engaging openers. Ofcourse, other types of product distribution machines and particulatematerials can be utilized.

Seeder 100 comprises a seed cart 110 towed between, for example, asupport vehicle such as a tractor (not shown) and a tilling implement112. The support vehicle includes a propulsion system for propelling orotherwise moving the vehicle over or relative to a terrain. Therefore,the propulsion system can be any propulsion system that is suitable tothe particular machine. In a case of a tractor or other similar supportmachine, the propulsion system can comprise an engine with atransmission that drives ground-engaging mechanisms such as wheels,tracks, etc.

The seed cart 110 includes a frame 114 to which product tanks 116 andwheels 118 are mounted. Each product tank 116 includes an associatedmetering system 120 at its lower end for controlled feeding of a productinto a pneumatic distribution system 122. The metering system 120 isadjacent to a discharge end of a product tank 116. The tilling implement112, towed behind the seed cart 110, comprises a frame 130 to which aplurality of row units are mounted. In the illustrated example, each rowunit comprises a ground opener 132. Incorporation of seed row finishingequipment, such as closing wheels 134, can also be utilized, in oneexample.

Metering system 120 is controllable to change the seed metering rateinto pneumatic distribution system 122, and thus the rate at which seedsflow to openers 132. Metering system 120 can be driven and/or controlledelectronically, hydraulically, pneumatically, a combination thereof,etc.

Pneumatic distribution system 122 includes an air source 136, such as,but not limited to, a fan, blower, compressor, and/or pump. In theillustrated example, air source 136 comprises a centrifugal fan (alsoreferred to as centrifugal fan 136) connected to a plenum 138, which inturn is connected through one or more conduits to one or more primarydistribution manifolds 124. Each manifold 124 is configured to receiveproduct from one of product tanks 116 that is metered through meteringsystem 120.

In one example, metering system 120 comprises one or more volumetricmeters that volumetrically meter product into distribution system 122.Volumetric meters are commonly used in agricultural equipment, such asgrain drills, air seeders or fertilizer applicators, to meter product(e.g. seed, fertilizer, etc.) during distribution. In one example, avolumetric meter employs one or more metering rollers contained within ahousing. The housing has an inlet that receives product from the tank.The tank feeds the product into the housing utilizing a deliverymechanism (e.g. air, gravity, feed mechanisms, etc.). In one particularexample, the tank is located above the housing and product is fed intothe housing using gravity.

Each individual passage in the primary distribution manifold 124 isconnected by a primary distribution line 140 to a riser tube 142, whichis in turn coupled to a secondary distribution header 144. Header 144operates as a splitter, to split the seed flow from primary distributionline 140 into a plurality of secondary distribution lines 146. Eachsecondary distribution line 146 is coupled to one (or more) seed bootmounted on one (or more) ground opener 132 to deliver the seed to afurrow formed by the opener 132. The seed flow rate, or seed count,along each secondary distribution line 146 can be sensed using one ormore seed sensors.

In the illustrated example, a plurality of distribution streams areformed and comprise a plurality of lines, or runs, to row units on airseeder 100. As used herein, a “line” refers to a channel or path. Forinstance, a line can provide a seed path to one or more row units havingfurrow opener(s). Further, a line can be formed by a plurality ofseparate elements connected together. For instance, a line can compriseseparate conduit(s), tube(s), manifold(s), meter(s), row unit(s), etc.,coupled together to form a single distribution path to an end point.

While seeder 100 of FIG. 1 is shown as a separate seed cart 110connected to tilling implement 112, in one example, the product tank116, metering system 120 and pneumatic distribution system 122 can bemounted on the same frame as the ground openers 132.

FIG. 2 is a top view of another example of an agricultural productdistribution machine for distributing agricultural product in the formof seed or other particulate material. In the illustrated example, themachine comprises a row crop planting machine 200 that illustrativelyincludes a toolbar 202 that is part of a frame 204. FIG. 2 also showsthat a plurality of planting row units 206 are mounted to the toolbar202. Machine 200 can be towed behind another machine, such as a tractor.

In one example, each row unit includes one or more tanks (e.g., chemicaltank, seed storage tank, etc.). It also illustratively includes a discopener, a set of gauge wheels, and a set of closing wheels. Seeds fromthe seed storage tank are fed by gravity into a seed meter. The seedmeter controls the rate at which seeds are dropped into a seed tube, orother seed distribution line, from the seed storage tank. The seed flowrate, or seed count, along the distribution line is sensed using one ormore seed sensors.

It will be noted that different types of seed meters can be utilized. Inone example, each row unit need not have its own seed meter. Instead,metering or other singulation or seed dividing techniques can beperformed at a central location, for groups of row units 106. Themetering systems can include rotatable discs, rotatable concave orbowl-shaped devices, among others. The seed delivery system can be agravity drop system in which seeds are dropped through the seed tube 120and fall (via gravitational force) through the seed tube into the seedtrench. Other types of seed delivery systems are assistive systems, inthat they do not simply rely on gravity to move the seed from themetering system into the ground. Instead, such systems actively capturethe seeds from the seed meter and physically move the seeds from themeter to a lower opening, where they exit into the ground or trench.

FIG. 3 is a schematic diagram illustrating one example of anagricultural machine architecture 300 including an agricultural machine301. Examples of agricultural machine 301 include, but are not limitedto, agricultural machines 100 and 200 illustrated in FIGS. 1 and 2,respectively.

Machine 301 includes a seed metering system 302 configured to meterseeds from a seed source 304. Seed metering system 302 meters the seeds,through a seed distribution system 306, to a plurality of distributionend point components. In the present example, the end point componentscomprise a plurality of row units 308.

In the present example, seed metering system 302 includes a plurality ofvolumetric meters 310-1, 310-2, 310-3, 310-4 (collectively referred toas volumetric meters 310), each configured to volumetrically meter seedsto a different section of the row units 308. In the illustrated example,agricultural machine includes thirty-two row units, divided into foursections (i.e., 312, 314, 316, 318) of eight row units each. This, ofcourse, is by way of example only. Agricultural machine 301 can includemore or less row units 308 and volumetric meters 310.

Volumetric meter 310-1 illustratively meters seeds through distributionsystem 306 to section 312 of eight row units, illustrated in FIG. 3 asrow units 312-1, 312-2, 312-3, 312-4, 312-5, 312-6, 312-7 and 312-8.Similarly, volumetric meter 310-2 meters seed through distributionsystem 306 to section 314 of eight row units (in FIG. 3, only four rowunits 314-1, 314-2, 314-3, 314-4 are shown). For sake of illustration,the third and fourth sections are generally represented by blocks 317and 319, respectively. As such, in this example, each volumetric meter310 meters product to a section of the row units that comprisesone-fourth of row units 308.

Distribution system 306 comprises a plurality of distribution lines thatconvey the metered seed from volumetric meters 310 to row units 308. Asdiscussed in further detail below, a seed metering and control system320 is configured to sense the seed flow rate along the distributionlines. Before discussing seed sensing and control system 320 in furtherdetail, it is noted that in the present example distribution system 306comprises a plurality of primary distribution lines that receive meteredproduct from volumetric meters 310 and convey the metered seed to asplitter component (e.g., header 144 illustrated in FIG. 1) which splitsthe seed into a plurality of secondary distribution lines that provide aseed flow path to the row units 308. In the illustrated example,volumetric meter 310-1 meters seed into primary distribution lines 322,324, 326, and 328, which are coupled to respective splitter components330, 332, 334, and 336 which split the flows into secondary distributionlines 338 and 340, 342 and 344, 346 and 348, and 350 and 352.

Similarly, volumetric meter 310-2 meters product into primarydistribution lines 356, 358, 360, and 362 which are coupled to splittercomponents that split the primary distribution lines into a plurality ofsecondary distribution lines.

System 320 comprises a set of seed sensors 364 associated with thedistribution lines to row units 308 and are configured to sense the flowrate or count of seeds (and thus the seeding rate) for the row units308. This provides an indication as to the rate at which the seeds arebeing dispersed into the ground (e.g., into a furrow formed in theground by the row units 308). Before discussing operation of the seedsensors in further detail, a discussion of other components of system320 will be provided.

System 320 illustratively includes a controller component 366 configuredto receive signals from sensors 364. Controller component 366 caninclude one or more controllers. Illustratively, but not by limitation,controller component 366 includes a primary controller 368 and a set ofsecondary controllers, each corresponding to a particular one of thesections 312, 314, 316, 318 and configured to receive signals from thesensors in the corresponding section. That is, as shown in FIG. 3, asecondary controller 370 corresponds to, and is configured to receivesensor signals from, section 312 and a secondary controller 372corresponds to, and is configured to receive signals from the sensors insection 314. The secondary controllers for sections 316 and 318 are notillustrated in FIG. 3, for the sake of brevity.

Secondary controllers 370 and 372 are configured to communicate withprimary controller 368, which includes a control signal (or action)generator 374. Control signal generator 374 is configured to generatecontrol signals that control operation of various aspects ofagricultural machine 301. Examples include, but are not limited to,control signals for a machine propulsion system, seed metering system302, distribution system 306, sensors 364, a communication component 376and/or a user interface component 376.

Communication component 376 includes wireless communication (or othertypes of communication) logic, and can include other items as well.Using wireless communication logic, communication component 376facilitates communication over a network, which can be a wide variety ofdifferent types of networks, such as the Internet, or another wide areanetwork, a variety of other wireless or wired networks, etc. Wirelesscommunication logic can be substantially any wireless communicationsystem that can be used by the systems and components of machine 301 tocommunicate information to other items in machine 301 and/or to remotesystem(s) 380.

Remote system(s) 380 can be a wide variety of different types ofsystems. For example, remote system can be a remote server environment,remote computer system that may be used, for instance, by a farmer, afarm manager, etc. Further, it can be a remote computing system, such asa mobile device, remote network, or a wide variety of other remotesystems.

System 320 also includes a data store 382, one or more processors 384,and it can include other items 386 as well.

User interface component 378 is configured to generate or otherwiseprovide user interface(s) 388, that facilitate interaction with a user390. A user interface 388 can include display(s) 392 generated, forexample, in an operator compartment of machine 301. User interface(s)388 can include other types of input/output (I/O) mechanisms 393 aswell.

Referring again to controller component 366, a correlation generationcomponent is configured to receive signals from a set of the seedsensors 346 and to generate a correlation between those sensors, whichis then applied by a correlation application component to extrapolateseed flow rates. This is discussed in further detail below. In theexample of FIG. 3, secondary controller 370 includes a correlationgeneration component 394 and a correlation application component 395.Secondary controller 372 includes a correlation generation component 396and a correlation application component 397. The generated correlationscan be stored in data store 392. This is represented by block 398. Datastore 382 can store the sensor information 399 from sensors 364, and canstore other items as well.

It is noted that while controller component 366 is illustrated as havingmultiple controllers and components that correspond to differentsections on machine 301, the functionality ascribed to each block can becombined and/or further separated and performed by other components. Forinstance, a single controller can receive the sensor signals from allsensors 364 and generate and apply the correlations, as well as generatethe control signal for machine 301.

As also illustrated in FIG. 3, each secondary distribution line to a rowunit 308 comprises at least one sensor (referred to as a “first” seedsensor, for the sake of the present discussion) on the distribution lineconfigured to sense a flow rate of seeds through that distribution line.It is noted that reference herein to the seed sensor as a “first” seedsensor is not intended to imply that the distribution line has a secondseed sensor. Further, it is noted that the seed sensors can be anysuitable sensor type(s) including, but not limited, optical sensorshaving optical components such as LED(s) (or other light source(s)) andone or more optical reads configured to sense the passage of seedsthrough the distribution line.

As shown in FIG. 3, a set of first sensors 402 includes sensors 404,406, 408, 410, 412, 414, 416, 418, 420, 422, 424, and 426. In oneexample, some or all of the first seed sensors 402 are substantiallysimilar to one another (e.g., they have substantially similar sensingprecisions). By substantially similar sensing precisions, it is meantthat the seed sensors are configured such that they each have a sensingprecision within ten percent of one another for a given flow rate. Inone example, substantially similar seed sensors have sensing precisionswithin five percent of each other. In one example, the substantiallysimilar seed sensors have the same sensing precision.

Further, in the present example, the first seed sensors have componentsthat are considered to be low precision or rate, in terms of theirmaximum seed flow sensing capabilities. In one example, the sensingprecision of a given seed sensor is defined by the maximum seed flowrate (e.g., seeds per second (seeds/sec) that the seed sensor can sensewithin a defined threshold error rate (e.g., twenty percent, tenpercent, five percent, etc.). The error rate comprises the deviation ofthe measured rate from the actual rate.

For sake of the present discussion, a low precision seed sensor has amaximum seed sensing rate less than approximately one hundred seeds/sec.That is, the error rate of the low precision sensor exceeds thethreshold error rate for seed flow rates above approximately one hundredseeds/sec. In one particular example, the low precision seed sensorshave a maximum seed sensing rate at (or less than) approximately fiftyseeds/sec with an error rate at (or less than) approximately twentypercent.

A low precision seed sensor can provide a relatively accurate measure ofseed flow rate for actual seed flows at or below its maximum seedsensing rates. For higher seed flow rates that exceed the maximum seedsensing rate, the error rate of the low precision seed sensor issignificantly higher. Thus, while a low precision sensor can be utilizedfor blockage sensing at high seed flow rates, they often do not providean otherwise meaningful measure of the actual flow rate. For sake ofillustration, but not by limitation, assume a set of low precision seedsensors, with a maximum seed sensing rates of fifty seed/sec, areutilized on a set of distribution lines that each convey two hundredseeds/sec (or more—some seeding applications use rates up to six hundredseeds/sec). However, the optical component(s) of one of the lowprecision seed sensors in a first distribution line outputs a firstsignal indicating that seventy five particles per second where sensed(this deviation can be caused by, for example, multiple seeds beingmisinterpreted as a single seed, seeds being missed, etc.), and theoptical component(s) of another one of the low precision seed sensors ina second distribution line outputs a second signal indicating that tenparticles per second where sensed. While the first signal is not anaccurate representation of the actual seed flow rate, it can be utilizedto determine that the second distribution line is experiencing ananomaly, which may be caused by a blockage or some other malfunction inthe metering and/or distribution system.

In the illustrated example, the seed sensing system comprises a secondseed sensor (i.e., sensors 428, 430, 432, 434), in addition to the firstseed sensor, on at least one of the distribution lines. The second seedsensor has a higher sensing precision compared to the first seed sensor.That is, the second seed sensor is on the same distribution line as, andis in series with, a first seed sensor and has a higher maximum seedsensing precision than the first seed sensor. In one example, themaximum seed sensing rate of the second (e.g., high precision) seedsensor is at least four times higher than the first (e.g., lowprecision) seed sensor. For instance, the maximum seed sensing rate ofthe second sensor is six to eight times higher than the first seedsensor. In another particular example, the maximum seed sensing rate ofthe second seed sensor is ten times higher than the first seed sensor.In one particular example, a second seed sensor has a maximum seedsensing rate of four hundred seeds/sec, or more.

The signal from the second seed sensor, on a particular one of thedistribution lines, is utilized by a correlation generation component(i.e., component 394, 396) to correlate the signal to the sensor signalreceived from the first seed sensor on the same particular distributionline. As such, the sensor signal from the first sensor (e.g., lowprecision sensor) provides a signal that is relatively inaccurate, butthe signal from the second seed sensor (e.g., high precision seedsensor) is then utilized to generate a correlation metric that can beapplied to the first sensor signal to give an improved (i.e., moreaccurate) indication of the actual seed flow rate.

Accordingly, in the illustrated example, a correlation metric can begenerated from the first and second seed sensors in a first one of thedistribution lines, and then applied to the sensor signal from one ormore other distribution lines that only have a low precision seedsensor, or at least do not have a high precision seed sensor. Thecorrelation metric can thus be utilized for seed rate extrapolationacross low precision sensors to provide improved seed rate detection,without requiring a high precision sensor to be installed on all of thedistribution lines.

In the illustrated example, each section 312, 314, 316, 318 includes atleast one second sensor on at least one of the distribution lines inthat section. The sensor signal from that second sensor is provided tothe correlation generation component in the secondary controllerassociated with that section and then used to generate a correlationmetric for that section, which is applied by the correlation applicationcomponent to the sensor signal from the first sensor on the otherdistribution lines in that section. In the illustrated example, twosecond sensors (428 and 430, 432 and 434) are provided in each section,and are on distribution lines associated with a same splitter component.This can be utilized to provide correlation metrics that are utilized bythe controller component 366 to determine operational characteristicsindicative of how well the splitter component is operating and/or can becombined to generate an average (or otherwise combined) rate offset tobe applied to the sensor signals from the other distribution lines.

FIG. 4 illustrates an example method 450 for generating correlationmetrics. For sake of illustration, but not by limitation, method 450will be discussed with respect to architecture 300 shown in FIG. 3.

At block 452, seed distribution system 306 is operated to distributeseed along distribution lines to row units 308. This includes meteringsystem 302 metering seed at a set application rate (e.g., a rate set byuser 390 via user interfaces 388). Volumetric meter 310-1 operates tometer seed into primary distribution lines 322, 324, 326, and 328. Thisis represented by block 453.

At block 454, the seed flow rate is sensed by the first sensor (e.g.,low precision sensor) on a given one of the distribution lines. Forinstance, secondary controller 370 receives a first sensor signal fromthe first sensor 404 on distribution line 338. This is represented byblock 456.

At block 458, the seed flow rate is sensed with a second sensor (e.g., ahigh precision sensor) on the same distribution line. For instance, inthe above example, secondary controller 370 receives a second sensorsignal from second sensor 428 on distribution line 338. This isrepresented by block 460.

At block 462, correlation generation component 394 generates acorrelation metric or value that represents a correlation between thefirst and second sensor signals received from first sensor 404 andsecond sensor 428. The generated correlation metric is tagged with anidentifier that identifies (or is otherwise associated with) at leastthe first sensor from which the correlation metric was generated. Forsake of illustration, assume that the first sensor signal from firstsensor 404 indicates a sensed flow rate of eighty-five seeds/sec and thesecond sensor signal from second sensor 428 indicates a sensed flow rateof two hundred twenty five seeds/sec. The generated correlation metricwould be associated with sensor 404 and indicate the correlation betweenthese two sensed flow rates. That is, application of the correlationmetric to the sensed rate of eighty-five seeds/sec obtains a finalmeasured rate of two hundred twenty five seeds/sec.

At block 464, the method determines whether there are any more lines forwhich to generate correlations. For example, block 464 determines that asecond distribution line 340 includes first and second sensors (406 and430) for which to generate a correlation metric. In this case, blocks454-462 are repeated for the sensor signals from sensors 406 and 430 ondistribution line 340. Block 464 can also perform steps 454-462 forsensors in other sections, such as sensors 420, 432, 422, and 434 insection 314.

If multiple correlation metrics are generated in a same section, or areotherwise associated with one another, the correlation metrics can becombined at block 466. In one example, the correlation metrics can beaveraged to create a rate offset at block 468. For sake of illustration,correlation generation component 394 generates a first correlationmetric based on the sensor signals from sensors 404 and 428 andgenerates a second correlation metric based on the signals received fromsensors 406 and 430. Component 394 can combine these by averaging,weighting, or otherwise, to generate a rate offset. The correlationmetrics can be combined in other ways as well. This is represented byblock 470.

At block 472, the correlation metric is utilized. This can be done in awide variety of ways. In one example, the correlation metric is appliedat block 474. One example of applying the correlation metric isdiscussed below with respect to FIG. 5. Briefly, however, thecorrelation metric can be applied to extrapolate flow rates at block476, calibrate one or more of the sensors at block 478, or in other ways(block 480) as well.

The correlation metric can be stored at block 482, such as in data store382 as correlations 398 that includes tag information that identifiersthe sensor(s) that the correlation metric is associated with. At block484, the correlation metric can be sent to remote system(s) 380 forstorage and/or analysis. The correlation metric can be utilized in otherways as well. This is represented at block 486.

FIG. 5 illustrates an example method 500 for applying a correlationmetric to a seed sensor signal to extrapolate seed flow rate. For sakeof illustration, but not by limitation, method 500 will be discussedwith respect to architecture 300 shown in FIG. 3.

At block 502, seed distribution system 306 is operated to distributeseed along distribution lines to row units 308. This includes meteringsystem 302 metering seed at a set application rate (e.g., a rate set byuser 390 via user interface(s) 388). Volumetric meter 310-1 operates tometer seed into primary distribution lines 322, 324, 326, and 328. Thisis represented by block 503.

At block 504, a seed rate is sensed with a first seed sensor (e.g., alow precision seed sensor) on a given distribution line. For sake of thepresent discussion, secondary controller 370 receives a signal from thefirst seed sensor 408 on distribution line 342. This is represented byblock 506.

At block 508, correlation application component 395 obtains acorrelation metric that is associated with a sensor that is the same orsimilar as the sensor from which the signal is received at block 504. Inthis example, correlation application component 395 obtains acorrelation metric (e.g., from stored correlations 398 or otherwise)that was generated using the sensor signal from sensor 404. Thus, thecorrelation metric was generated from another substantially similarsensor on the same machine section. This is represented by block 510.Alternatively, or in addition, the correlation metric obtained at block508 can be obtained from a substantially similar sensor on a differentsection of machine 301. This is represented by block 512. The similarsensor can be a sensor having similar sensing characteristics (e.g., asimilar sensing precision and/or similar maximum sensing rate), and canbe of the same type and/or manufacturer/model.

At block 514, the correlation metric obtained at block 508 is applied tothe first sensor signal obtained at block 504 to extrapolate the seedflow rate on the distribution line. In the present example, the seedflow rate on line 342 is extrapolated by applying the correlation metricto the sensor signal received from sensor 408.

By way of example, but not by limitation, assume the sensor signal fromsensor 408 indicates a seed flow rate of ninety-two seeds/sec. Byapplying the correlation metric at block 514, correlation applicationcomponent 395 determines that the extrapolated seed flow rate on line342 is two hundred forty-five seeds/sec. This, of course, is by way ofillustrative example only. In any case, the extrapolated seed flow ratecan be utilized at block 516 to generate a control signal to controlagricultural machine 301.

In one example, control signal generator 374 generates a control signalto control seed metering system 302. This includes, but is not limitedto, changing settings to increase or decrease the rate at whichvolumetric meter 310-1 is metering seeds into distribution lines 322,324, 326, and 328. This is represented at block 518.

At block 520, control signal generator 374 generates a controlinstruction that controls user interface component 378 to generate auser interface 388 that indicates the seed flow rate that is determinedat block 514. For instance, the seed flow rate extrapolated for line 342can be rendered to user 390 through display(s) 392, along with anindication that indicates a deviation from a user-defined desired flowrate. As such, the user can manually adjust the settings of seedmetering system 302 based on the indication.

At block 522, control signal generator 374 can control communicationcomponent 376 to send an indication to remote system(s) 380, forexample. A control signal can be generated in other ways and/or tocontrol other components/systems as well. This is represented by block524.

At block 526, the method determines whether there are any additionaldistribution lines for which to extrapolate seed flow rates. In theillustrated example, steps 504-516 are repeated for distribution lines346, 348, 350, 352, and 354, utilizing the correlation metric that isobtained based on the sensor signals from sensors 404 and/or 406.

It can thus be seen that the present system provides a number ofadvantages. For example, the present system provides a seed sensingsystem that generates correlation metrics between seed sensors that canbe applied to seed sensing signals to improve the accuracy of seed flowrate/quantity detection. Further, by obtaining the correlation metricsusing higher quality seed sensors, the correlation metrics can beapplied to signals from lower quality seed sensors to generate animproved, or at least more accurate, indication of the seed flow rate,without having to install additional high precision sensors on eachdistribution line. This reduces the complexity and cost in implementingthe seed sensing system. Further, the control systems/actions generatedbased on the operation of the seed sensing system are also improved.

It will be noted that the above discussion has described a variety ofdifferent systems, components and/or logic. It will be appreciated thatsuch systems, components and/or logic can be comprised of hardware items(such as processors and associated memory, or other processingcomponents, some of which are described below) that perform thefunctions associated with those systems, components and/or logic. Inaddition, the systems, components and/or logic can be comprised ofsoftware that is loaded into a memory and is subsequently executed by aprocessor or server, or other computing component, as described below.The systems, components and/or logic can also be comprised of differentcombinations of hardware, software, firmware, etc., some examples ofwhich are described below. These are only some examples of differentstructures that can be used to form the systems, components and/or logicdescribed above. Other structures can be used as well.

The present discussion has mentioned processors and servers. In oneexample, the processors and servers include computer processors withassociated memory and timing circuitry, not separately shown. They arefunctional parts of the systems or devices to which they belong and areactivated by, and facilitate the functionality of the other componentsor items in those systems.

Also, a number of user interface displays have been discussed. They cantake a wide variety of different forms and can have a wide variety ofdifferent user actuatable input mechanisms disposed thereon. Forinstance, the user actuatable input mechanisms can be text boxes, checkboxes, icons, links, drop-down menus, search boxes, etc. They can alsobe actuated in a wide variety of different ways. For instance, they canbe actuated using a point and click device (such as a track ball ormouse). They can be actuated using hardware buttons, switches, ajoystick or keyboard, thumb switches or thumb pads, etc. They can alsobe actuated using a virtual keyboard or other virtual actuators. Inaddition, where the screen on which they are displayed is a touchsensitive screen, they can be actuated using touch gestures. Also, wherethe device that displays them has speech recognition components, theycan be actuated using speech commands.

A number of data stores have also been discussed. It will be noted theycan each be broken into multiple data stores. All can be local to thesystems accessing them, all can be remote, or some can be local whileothers are remote. All of these configurations are contemplated herein.

Also, the figures show a number of blocks with functionality ascribed toeach block. It will be noted that fewer blocks can be used so thefunctionality is performed by fewer components. Also, more blocks can beused with the functionality distributed among more components.

FIG. 6 is a block diagram illustrating architecture 300, shown in FIG.3, except that it (or portions thereof) is deployed in a remote serverarchitecture 600. In an example, remote server architecture 600 canprovide computation, software, data access, and storage services that donot require end-user knowledge of the physical location or configurationof the system that delivers the services. In various embodiments, remoteservers can deliver the services over a wide area network, such as theinternet, using appropriate protocols. For instance, remote servers candeliver applications over a wide area network and they can be accessedthrough a web browser or any other computing component. Software orcomponents shown in FIG. 3 as well as the corresponding data, can bestored on servers at a remote location. The computing resources in aremote server environment can be consolidated at a remote data centerlocation or they can be dispersed. Remote server infrastructures candeliver services through shared data centers, even though they appear asa single point of access for the user. Thus, the components andfunctions described herein can be provided from a remote server at aremote location using a remote server architecture. Alternatively, theycan be provided from a conventional server, or they can be installed onclient devices directly, or in other ways.

In the example shown in FIG. 6, some items are similar to those shown inFIG. 3 and they are similarly numbered. FIG. 6 specifically shows thatone or more of remote system 380 or seed metering and control system 320can be located at a remote server location 602. The information can beprovided to remote server location 602 by machine 301 (e.g., from system320) in any of a wide variety of different ways. Therefore, user 390and/or machine 301 can access those systems through remote serverlocation 602. This can be done using a user device 604, for instance.

FIG. 6 also depicts another embodiment of a remote server architecture.FIG. 6 shows that it is also contemplated that some elements of FIG. 3are disposed at remote server location 602 while others are not. By wayof example, data store 382 can be disposed at a location separate fromlocation 602, and accessed through the remote server at location 602. Inanother example, system 302 (or portions thereof) can be disposed at alocation separate from location 602, and accessed through the remoteserver at location 602. In another example, system 320 can be disposedat a location separate from location 602, and accessed through theremote server at location 602. Regardless of where they are located,they can be accessed directly by user device 604, through a network(either a wide area network or a local area network), they can be hostedat a remote site by a service, or they can be provided as a service, oraccessed by a connection service that resides in a remote location.Also, the data can be stored in substantially any location andintermittently accessed by, or forwarded to, interested parties. Forinstance, physical carriers can be used instead of, or in addition to,electromagnetic wave carriers. In such an embodiment, where cellcoverage is poor or nonexistent, another mobile machine (such as a fueltruck) can have an automated information collection system. As themachine comes close to the fuel truck for fueling, the systemautomatically collects the information from the harvester using any typeof ad-hoc wireless connection. The collected information can then beforwarded to the main network as the fuel truck reaches a location wherethere is cellular coverage (or other wireless coverage). For instance,the fuel truck may enter a covered location when traveling to fuel othermachines or when at a main fuel storage location. All of thesearchitectures are contemplated herein. Further, the information can bestored on machine 301 until the machine enters a covered location. Themachine, itself, can then send the information to the main network.

It will also be noted that the elements of architecture 300 shown inFIG. 3, or portions thereof, can be disposed on a wide variety ofdifferent devices. Some of those devices include servers, desktopcomputers, laptop computers, tablet computers, or other mobile devices,such as palm top computers, cell phones, smart phones, multimediaplayers, personal digital assistants, etc.

FIG. 7 is a simplified block diagram of one illustrative example of ahandheld or mobile computing device that can be used as a user's orclient's hand held device 16, in which the present system (or parts ofit) can be deployed. For instance, a mobile device can be deployed inthe operator compartment of machine 301, or as user device 604 for usein generating, processing, or displaying the plant evaluationinformation. FIGS. 8-9 are examples of handheld or mobile devices.

FIG. 7 provides a general block diagram of the components of a clientdevice 16 that can run some components shown in FIG. 3, that interactswith them, or both. In the device 16, a communications link 13 isprovided that allows the handheld device to communicate with othercomputing devices and under some embodiments provides a channel forreceiving information automatically, such as by scanning. Examples ofcommunications link 13 include allowing communication though one or morecommunication protocols, such as wireless services used to providecellular access to a network, as well as protocols that provide localwireless connections to networks.

In other examples, applications can be received on a removable SecureDigital (SD) card that is connected to an interface 15. Interface 15 andcommunication links 13 communicate with a processor 17 (which can alsoembody any processor or server from previous Figures) along a bus 19that is also connected to memory 21 and input/output (I/O) components23, as well as clock 25 and location system 27.

I/O components 23, in one embodiment, are provided to facilitate inputand output operations. I/O components 23 for various embodiments of thedevice 16 can include input components such as buttons, touch sensors,optical sensors, microphones, touch screens, proximity sensors,accelerometers, orientation sensors and output components such as adisplay device, a speaker, and or a printer port. Other I/O components23 can be used as well.

Clock 25 illustratively comprises a real time clock component thatoutputs a time and date. It can also, illustratively, provide timingfunctions for processor 17.

Location system 27 illustratively includes a component that outputs acurrent geographical location of device 16. This can include, forinstance, a global positioning system (GPS) receiver, a LORAN system, adead reckoning system, a cellular triangulation system, or otherpositioning system. It can also include, for example, mapping softwareor navigation software that generates desired maps, navigation routesand other geographic functions.

Memory 21 stores operating system 29, network settings 31, applications33, application configuration settings 35, data store 37, communicationdrivers 39, and communication configuration settings 41. Memory 21 caninclude all types of tangible volatile and non-volatilecomputer-readable memory devices. It can also include computer storagemedia (described below). Memory 21 stores computer readable instructionsthat, when executed by processor 17, cause the processor to performcomputer-implemented steps or functions according to the instructions.Processor 17 can be activated by other components to facilitate theirfunctionality as well.

FIG. 8 shows one embodiment in which device 16 is a tablet computer 700.In FIG. 8, computer 700 is shown with user interface display screen 702.Screen 702 can be a touch screen or a pen-enabled interface thatreceives inputs from a pen or stylus. It can also use an on-screenvirtual keyboard. Of course, it might also be attached to a keyboard orother user input device through a suitable attachment mechanism, such asa wireless link or USB port, for instance. Computer 700 can alsoillustratively receive voice inputs as well.

FIG. 9 shows that the device can be a smart phone 71. Smart phone 71 hasa touch sensitive display 73 that displays icons or tiles or other userinput mechanisms 75. Mechanisms 75 can be used by a user to runapplications, make calls, perform data transfer operations, etc. Ingeneral, smart phone 71 is built on a mobile operating system and offersmore advanced computing capability and connectivity than a featurephone.

Note that other forms of the devices 16 are possible.

FIG. 10 is one example of a computing environment in which elements ofFIG. 3, or parts of it, (for example) can be deployed. With reference toFIG. 10, an example system for implementing some embodiments includes ageneral-purpose computing device in the form of a computer 810.Components of computer 810 may include, but are not limited to, aprocessing unit 820 (which can comprise processors or servers from anyprevious Figure), a system memory 830, and a system bus 821 that couplesvarious system components including the system memory to the processingunit 820. The system bus 821 may be any of several types of busstructures including a memory bus or memory controller, a peripheralbus, and a local bus using any of a variety of bus architectures. Memoryand programs described with respect to FIG. 3 can be deployed incorresponding portions of FIG. 10.

Computer 810 typically includes a variety of computer readable media.Computer readable media can be any available media that can be accessedby computer 810 and includes both volatile and nonvolatile media,removable and non-removable media. By way of example, and notlimitation, computer readable media may comprise computer storage mediaand communication media. Computer storage media is different from, anddoes not include, a modulated data signal or carrier wave. It includeshardware storage media including both volatile and nonvolatile,removable and non-removable media implemented in any method ortechnology for storage of information such as computer readableinstructions, data structures, program modules or other data. Computerstorage media includes, but is not limited to, RAM, ROM, EEPROM, flashmemory or other memory technology, CD-ROM, digital versatile disks (DVD)or other optical disk storage, magnetic cassettes, magnetic tape,magnetic disk storage or other magnetic storage devices, or any othermedium which can be used to store the desired information and which canbe accessed by computer 810. Communication media may embody computerreadable instructions, data structures, program modules or other data ina transport mechanism and includes any information delivery media. Theterm “modulated data signal” means a signal that has one or more of itscharacteristics set or changed in such a manner as to encode informationin the signal.

The system memory 830 includes computer storage media in the form ofvolatile and/or nonvolatile memory such as read only memory (ROM) 831and random access memory (RAM) 832. A basic input/output system 833(BIOS), containing the basic routines that help to transfer informationbetween elements within computer 810, such as during start-up, istypically stored in ROM 831. RAM 832 typically contains data and/orprogram modules that are immediately accessible to and/or presentlybeing operated on by processing unit 820. By way of example, and notlimitation, FIG. 10 illustrates operating system 834, applicationprograms 835, other program modules 836, and program data 837.

The computer 810 may also include other removable/non-removablevolatile/nonvolatile computer storage media. By way of example only,FIG. 10 illustrates a hard disk drive 841 that reads from or writes tonon-removable, nonvolatile magnetic media, nonvolatile magnetic disk852, an optical disk drive 855, and nonvolatile optical disk 856. Thehard disk drive 841 is typically connected to the system bus 821 througha non-removable memory interface such as interface 840, and optical diskdrive 855 are typically connected to the system bus 821 by a removablememory interface, such as interface 850.

Alternatively, or in addition, the functionality described herein can beperformed, at least in part, by one or more hardware logic components.For example, and without limitation, illustrative types of hardwarelogic components that can be used include Field-programmable Gate Arrays(FPGAs), Application-specific Integrated Circuits (e.g., ASICs),Application-specific Standard Products (e.g., ASSPs), System-on-a-chipsystems (SOCs), Complex Programmable Logic Devices (CPLDs), etc.

The drives and their associated computer storage media discussed aboveand illustrated in FIG. 10, provide storage of computer readableinstructions, data structures, program modules and other data for thecomputer 810. In FIG. 10, for example, hard disk drive 841 isillustrated as storing operating system 844, application programs 845,other program modules 846, and program data 847. Note that thesecomponents can either be the same as or different from operating system834, application programs 835, other program modules 836, and programdata 837.

A user may enter commands and information into the computer 810 throughinput devices such as a keyboard 862, a microphone 863, and a pointingdevice 861, such as a mouse, trackball or touch pad. Other input devices(not shown) may include a joystick, game pad, satellite dish, scanner,or the like. These and other input devices are often connected to theprocessing unit 820 through a user input interface 860 that is coupledto the system bus, but may be connected by other interface and busstructures. A visual display 891 or other type of display device is alsoconnected to the system bus 821 via an interface, such as a videointerface 890. In addition to the monitor, computers may also includeother peripheral output devices such as speakers 897 and printer 896,which may be connected through an output peripheral interface 895.

The computer 810 is operated in a networked environment using logicalconnections (such as a local area network—LAN, or wide area network WAN)to one or more remote computers, such as a remote computer 880.

When used in a LAN networking environment, the computer 810 is connectedto the LAN 871 through a network interface or adapter 870. When used ina WAN networking environment, the computer 810 typically includes amodem 872 or other means for establishing communications over the WAN873, such as the Internet. In a networked environment, program modulesmay be stored in a remote memory storage device. FIG. 10 illustrates,for example, that remote application programs 885 can reside on remotecomputer 880.

It should also be noted that the different examples described herein canbe combined in different ways. That is, parts of one or more examplescan be combined with parts of one or more other examples. All of this iscontemplated herein.

Example 1 is an agricultural machine comprising:

-   -   a material distribution system comprising a material        distribution line configured to convey particulate material to a        component; and    -   a sensing system comprising:        -   a first sensor configured to generate a first sensor signal            indicative of a measure of a flow of the particulate            material in the material distribution line;        -   a second sensor configured to generate a second sensor            signal indicative of a measure of the flow of the            particulate material in the material distribution line; and        -   a correlation generation component configured to receive            indications of the first and second sensor signals and to            generate a correlation metric that represents a correlation            between the first and second sensor signals.

Example 2 is the agricultural machine of any or all previous examples,wherein

-   -   the material distribution line comprises a first material        distribution line configured to convey a first flow of        particulate material to a first component;    -   the material distribution system comprises a second material        distribution line configured to convey a second flow of        particulate material to a second component; and    -   the sensing system comprises:        -   a third sensor configured to generate a third sensor signal            indicative of a measure of the second flow of the            particulate material in the second material distribution            line; and        -   a correlation application component configured to determine            a rate of the second flow based on applying the correlation            metric to the third sensor signal.

Example 3 is the agricultural machine of any or all previous examples,wherein the first sensor and the third sensor have substantially similarsensing precision.

Example 4 is the agricultural machine of any or all previous examples,wherein the second sensor has a higher sensing precision compared to thethird sensor.

Example 5 is the agricultural machine of any or all previous examples,wherein the second sensor comprises a high precision sensor and thethird sensor comprises a low precision sensor.

Example 6 is the agricultural machine of any or all previous examples,wherein

-   -   the third sensor has an error rate above ten percent for        material flow rates above fifty particles per second, and    -   the determined rate of the second flow is greater than fifty        particles per second with an error rate at or less than        approximately ten percent.

Example 7 is the agricultural machine of any or all previous examples,wherein the determined rate of the second flow is greater than twohundred particles per second.

Example 8 is the agricultural machine of any or all previous examples,and further comprising:

-   -   a control component configured to generate a control signal that        controls the agricultural machine based on the determined rate.

Example 9 is the agricultural machine of any or all previous examples,wherein the control signal controls a metering system configured tometer the particulate material into the second material distributionline.

Example 10 is the agricultural machine of any or all previous examples,wherein

-   -   the particulate material comprises seeds,    -   the component comprising a row unit configured to disburse the        seeds onto a terrain, and    -   the material distribution system comprising an air source        providing an air stream to pneumatically convey the seeds along        the material distribution line to the row unit.

Example 11 is the agricultural machine of any or all previous examples,wherein the second sensor has a higher sensing precision compared to thefirst sensor.

Example 12 is the agricultural machine of any or all previous examples,wherein the second sensor has a maximum sensing rate that is at leastfour times greater than a maximum sensing rate of the first sensor.

Example 13 is the agricultural machine of any or all previous examples,wherein the first sensor comprises a low precision sensor and the secondsensor comprises a high precision sensor.

Example 14 is the agricultural machine of any or all previous examples,wherein

-   -   the correlation metric comprises a first correlation metric;    -   the material distribution line comprises a first material        distribution line configured to convey a first flow of        particulate material to a first component;    -   the material distribution system comprises:        -   a second material distribution line configured to convey a            second flow of particulate material to a second component;            and    -   the sensing system comprises:        -   a third sensor configured to generate a third sensor signal            indicative of a measure of the second flow; and        -   a fourth sensor configured to generate a fourth sensor            signal indicative of a measure of the second flow; and    -   the correlation generation component is configured to:        -   generate a second correlation metric that represents a            correlation between the third sensor signal and the fourth            sensor signal; and        -   generate a rate offset metric based on the first and second            correlation metrics.

Example 15 is the agricultural machine of any or all previous examples,wherein

-   -   the material distribution system comprises:        -   a primary distribution line that receives particulate            material from a metering system; and        -   a splitter component configured to split the particulate            material from the primary distribution line into the first            material distribution line and the second material            distribution line;        -   a third material distribution line configured to convey a            third flow of particulate material to a third distribution            end point component;    -   the sensing system comprises:        -   a fifth sensor configured to generate a fifth sensor signal            indicative of a measure of the third flow; and        -   a correlation application component configured to determine            a rate of the third flow by applying the rate offset metric            to the fifth sensor signal.

Example 16 is a method performed by an agricultural machine, the methodcomprising:

-   -   receiving a first sensor signal from a first sensor that senses        a first flow of particulate material along a first material        distribution line;    -   receiving a second sensor signal from a second sensor that        senses the first flow of particulate material along the first        material distribution line;    -   generating a correlation metric that represents a correlation        between the first sensor signal and the second sensor signal;    -   receiving a third sensor signal from a third sensor that senses        a second flow of particulate material along a second material        distribution line;    -   determining a rate of the second flow by applying the        correlation metric to the third sensor signal; and    -   generating a control signal that controls the agricultural        machine based on the determined rate.

Example 17 is the method of any or all previous examples, wherein

-   -   the particulate material comprises seeds;    -   the first material distribution line conveys the first flow of        seeds to a first row unit;    -   the second material distribution line conveys the second flow of        seeds to a second row unit;    -   the first and third seed sensors comprise low precision sensors;        and    -   the second seed sensor comprises a high precision sensor.

Example 18 is an agricultural machine comprising:

-   -   a distribution system comprising:        -   a first distribution line configured to convey a first seed            flow to a first component; and        -   a second distribution line configured to convey a second            seed flow to a second component;    -   a metering system configured to meter seeds into the first and        second distribution lines;    -   a seed sensing system comprising:        -   a first seed sensor configured to generate a first sensor            signal indicative of the first seed flow;        -   a second seed sensor configured to generate a second sensor            signal indicative of the first seed flow;        -   a correlation generation component configured to receive            indications of the first and second sensor signals and            generate a correlation metric that represents a correlation            between the first sensor signal and the second sensor            signal;        -   a third seed sensor configured to generate a third sensor            signal indicative of the second seed flow; and        -   a correlation application component configured to determine            a rate of the second seed flow based on applying the            correlation metric to the third sensor signal; and    -   a control system configured to generate a control signal that        controls the agricultural machine based on the determined rate.

Example 19 is the agricultural machine of any or all previous examples,wherein the first and third seed sensors comprise low precision sensors,and the second seed sensor comprises a high precision sensor.

Example 20 is the agricultural machine of any or all previous examples,wherein

-   -   each of the first and second components comprise a row unit        configured to disburse the seed onto a terrain, and    -   the material distribution system comprises an air source        providing air streams to pneumatically convey seeds along the        first and second distribution lines to the row units.

Although the subject matter has been described in language specific tostructural features and/or methodological acts, it is to be understoodthat the subject matter defined in the appended claims is notnecessarily limited to the specific features or acts described above.Rather, the specific features and acts described above are disclosed asexample forms of implementing the claims.

What is claimed is:
 1. An agricultural machine comprising: a materialdistribution system comprising a material distribution line configuredto convey particulate material to a component; and a sensing systemcomprising: a first sensor configured to generate a first sensor signalindicative of a measure of a flow of the particulate material in thematerial distribution line; a second sensor configured to generate asecond sensor signal indicative of a measure of the flow of theparticulate material in the material distribution line; and acorrelation generation component configured to receive indications ofthe first and second sensor signals and to generate a correlation metricthat represents a correlation between the first and second sensorsignals.
 2. The agricultural machine of claim 1, wherein the materialdistribution line comprises a first material distribution lineconfigured to convey a first flow of particulate material to a firstcomponent; the material distribution system comprises a second materialdistribution line configured to convey a second flow of particulatematerial to a second component; and the sensing system comprises: athird sensor configured to generate a third sensor signal indicative ofa measure of the second flow of the particulate material in the secondmaterial distribution line; and a correlation application componentconfigured to determine a rate of the second flow based on applying thecorrelation metric to the third sensor signal.
 3. The agriculturalmachine of claim 2, wherein the first sensor and the third sensor havesubstantially similar sensing precision.
 4. The agricultural machine ofclaim 3, wherein the second sensor has a higher sensing precisioncompared to the third sensor.
 5. The agricultural machine of claim 3,wherein the second sensor comprises a high precision sensor and thethird sensor comprises a low precision sensor.
 6. The agriculturalmachine of claim 5, wherein the third sensor has an error rate above tenpercent for material flow rates above fifty particles per second, andthe determined rate of the second flow is greater than fifty particlesper second with an error rate at or less than approximately ten percent.7. The agricultural machine of claim 6, wherein the determined rate ofthe second flow is greater than two hundred particles per second.
 8. Theagricultural machine of claim 2, further comprising: a control componentconfigured to generate a control signal that controls the agriculturalmachine based on the determined rate.
 9. The agricultural machine ofclaim 8, wherein the control signal controls a metering systemconfigured to meter the particulate material into the second materialdistribution line.
 10. The agricultural machine of claim 1, wherein theparticulate material comprises seeds, the component comprising a rowunit configured to disburse the seeds onto a terrain, and the materialdistribution system comprising an air source providing an air stream topneumatically convey the seeds along the material distribution line tothe row unit.
 11. The agricultural machine of claim 1, wherein thesecond sensor has a higher sensing precision compared to the firstsensor.
 12. The agricultural machine of claim 11, wherein the secondsensor has a maximum sensing rate that is at least four times greaterthan a maximum sensing rate of the first sensor.
 13. The agriculturalmachine of claim 11, wherein the first sensor comprises a low precisionsensor and the second sensor comprises a high precision sensor.
 14. Theagricultural machine of claim 1, wherein the correlation metriccomprises a first correlation metric; the material distribution linecomprises a first material distribution line configured to convey afirst flow of particulate material to a first component; the materialdistribution system comprises: a second material distribution lineconfigured to convey a second flow of particulate material to a secondcomponent; and the sensing system comprises: a third sensor configuredto generate a third sensor signal indicative of a measure of the secondflow; and a fourth sensor configured to generate a fourth sensor signalindicative of a measure of the second flow; and the correlationgeneration component is configured to: generate a second correlationmetric that represents a correlation between the third sensor signal andthe fourth sensor signal; and generate a rate offset metric based on thefirst and second correlation metrics.
 15. The agricultural machine ofclaim 14, wherein the material distribution system comprises: a primarydistribution line that receives particulate material from a meteringsystem; and a splitter component configured to split the particulatematerial from the primary distribution line into the first materialdistribution line and the second material distribution line; a thirdmaterial distribution line configured to convey a third flow ofparticulate material to a third distribution end point component; thesensing system comprises: a fifth sensor configured to generate a fifthsensor signal indicative of a measure of the third flow; and acorrelation application component configured to determine a rate of thethird flow by applying the rate offset metric to the fifth sensorsignal.
 16. A method performed by an agricultural machine, the methodcomprising: receiving a first sensor signal from a first sensor thatsenses a first flow of particulate material along a first materialdistribution line; receiving a second sensor signal from a second sensorthat senses the first flow of particulate material along the firstmaterial distribution line; generating a correlation metric thatrepresents a correlation between the first sensor signal and the secondsensor signal; receiving a third sensor signal from a third sensor thatsenses a second flow of particulate material along a second materialdistribution line; determining a rate of the second flow by applying thecorrelation metric to the third sensor signal; and generating a controlsignal that controls the agricultural machine based on the determinedrate.
 17. The method of claim 16, wherein the particulate materialcomprises seeds; the first material distribution line conveys the firstflow of seeds to a first row unit; the second material distribution lineconveys the second flow of seeds to a second row unit; the first andthird seed sensors comprise low precision sensors; and the second seedsensor comprises a high precision sensor.
 18. An agricultural machinecomprising: a distribution system comprising: a first distribution lineconfigured to convey a first seed flow to a first component; and asecond distribution line configured to convey a second seed flow to asecond component; a metering system configured to meter seeds into thefirst and second distribution lines; a seed sensing system comprising: afirst seed sensor configured to generate a first sensor signalindicative of the first seed flow; a second seed sensor configured togenerate a second sensor signal indicative of the first seed flow; acorrelation generation component configured to receive indications ofthe first and second sensor signals and generate a correlation metricthat represents a correlation between the first sensor signal and thesecond sensor signal; a third seed sensor configured to generate a thirdsensor signal indicative of the second seed flow; and a correlationapplication component configured to determine a rate of the second seedflow based on applying the correlation metric to the third sensorsignal; and a control system configured to generate a control signalthat controls the agricultural machine based on the determined rate. 19.The agricultural machine of claim 18, wherein the first and third seedsensors comprise low precision sensors, and the second seed sensorcomprises a high precision sensor.
 20. The agricultural machine of claim19, wherein each of the first and second components comprise a row unitconfigured to disburse the seed onto a terrain, and the materialdistribution system comprises an air source providing air streams topneumatically convey seeds along the first and second distribution linesto the row units.